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Effective ecosystem-based management of bottom-contacting fisheries requires understanding of how disturbances from fishing affect seafloor fauna over a wide range of spatial and temporal scales. Spatial predictions of abundance for 67 taxa were developed, using an extensive dataset of faunal abundances collected using a towed camera system and spatially explicit predictor variables including bottom-trawl fishing effort, using a Joint Species Distribution Model (JSDM). The model fit metrics varied by taxon: the mean tenfold cross-validated AUC score was 0.70 ± 0.1 (standard deviation) for presence–absence and an R2 of 0.11 ± 0.1 (standard deviation) for abundance models. Spatial predictions of probability of occurrence and abundance (individuals per km2) varied by taxon, but there were key areas of overlap, with highest predicted taxon richness in areas of the continental shelf break and slope. The resulting joint predictions represent significant advances on previous predictions because they are of abundance, allow the exploration of co-occurrence patterns and provide credible estimates of taxon richness (including for rare species that are often not included in more commonly used single-species distribution modelling). Habitat-forming taxa considered to be Vulnerable Marine Ecosystem (VME) indicators (those taxa that are physically or functionally fragile to anthropogenic impacts) were identified in the dataset. Spatial estimates of likely VME distribution (as well as associated estimates of uncertainty) were predicted for the study area. Identifying areas most likely to represent a VME (rather than simply VME indicator taxa) provides much needed quantitative estimates of vulnerable habitats, and facilitates an evidence-based approach to managing potential impacts of bottom-trawling. [ABSTRACT FROM AUTHOR]

Recent outbreaks of the West Nile virus have been reported in southern Spain, a region with important wetland habitats for migratory birds. Here, we analyzed the role of species association and abiotic parameters on the abundance of seven mosquito species in the Doñana National Park, Spain. We applied the Joint Species Distribution Models (JSDM), using the Hierarchical Modeling of Species Communities approach to simultaneously model the effect of habitat type, normalized difference vegetation index, hydroperiod, distance to rivers, land surface temperature, and the abundance of seven mosquito species. We created three models with varied parameters and evaluated the effects of abiotic parameters and species-to-species associations, which served as proxies for species interactions. Our models estimated the species-specific responses of the mosquito community to abiotic parameters. A positive association was identified within the Culex community with potential biotic interactions. However, Ochlerotatus caspius, Ochlerotatus detritus, and Anopheles atroparvus had no statistically significant association with each other and with the Culex species after accounting for the effect of abiotic parameters. We also found that the potential species associations estimated at particular sites and abiotic parameters influenced the model projection for the average abundance of mosquito species. The JSDM will allow spatial projection of the abundance of each mosquito species, which is an important parameter for epidemiological models. The JSDM inference of species association is important because predation, competition, and facilitation affect the distribution and abundance of different species. [ABSTRACT FROM AUTHOR]

Many statistical methods attempt to detect species associations—and so infer interspecific interactions—from species co‐occurrence patterns. Habitat heterogeneity and out‐of‐equilibrium colonization histories are well recognized as potentially causing species associations, even when interactions are absent. The potential for patch disturbance, a classical component of metacommunity dynamics, to also drive spurious species associations has however been overlooked.Using a new general metacommunity model, we derive mathematical predictions regarding how patch disturbance would affect the patterns of species associations detected in 'null' co‐occurrence matrices. We also conduct numerical simulations to test our predictions and to compare the performance of several widespread statistical methods, including direct tests of pairwise independence, matrix permutation approaches and joint species distribution modelling.We show how classical metacommunity dynamics can produce statistical associations, both positive and negative, even when species do not interact, when there is no habitat heterogeneity, and at equilibrium. This occurs as soon as there is some rate of patch disturbance (i.e. simultaneous extinction of several species in a patch) and/or a finite life span of patches, a common feature of a broad range of plant, animal or microbial systems.Patch disturbance can compromise species co‐occurrence analyses and cause the artefactual detection of species associations if not taken into account. Including patch age (i.e. the time since the last patch disturbance event) as a covariate in a joint species distribution model can resolve the artefact. However, this requires additional data that often are not available in practice. We argue that the consequences of patch disturbance should not be underestimated when analysing species distribution patterns in metacommunity‐like systems. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

In this paper, a downlink (DL) precoding scheme is introduced for time-division-duplex (TDD) multi-cell multi-user 3D massive MIMO/full-dimension MIMO (FD-MIMO) systems. A pre-beamformer based on uplink direction-of-arrival (DoA) is incorporated with interference alignment (IA) scheme to provide more degrees of freedom for each cell. We analyze the feasible conditions of applying IA schemes and provide the corresponding precoding schemes for different inter-cell interference scenarios. Simulation results show that the introduced IA-DoA-based multi-cell multi-user precoding and power allocation scheme significantly outperform the existing IA-based precoding strategies for FD-MIMO systems. [ABSTRACT FROM AUTHOR]

Aim: Separating the biotic and abiotic factors controlling species distributions has been a long‐standing challenge in ecology and biogeography. Joint species distribution models (JSDMs) have emerged as a promising statistical framework towards this objective by simultaneously modelling the environmental responses of multiple species and approximating species associations based on patterns in their (co‐)occurrences. However, the signature of biotic interactions should be most evident at fine spatial resolutions. Here, we test how the resolution of input data affects the inferences from JSDMs. Location: Switzerland. Taxon: Birds. Methods: Using standardized survey data of 43 woodland bird species and 8 climatic, topographic and vegetation structural predictors, we fit JSDMs at different spatial resolutions (125–1000 m) and sampling periods (1 and 5 years). In addition, we calculate functional similarity among all species as an independent proxy of biotic interactions, specifically competition. We then assess how JSDM performance and estimates vary with the spatial resolution of the input data and test whether species associations are consistent across grain sizes and with the alternative approach based on functional similarity. Results: Our results show better model performance at coarser spatial resolutions and for longer sampling periods. Although pairwise species associations estimated in JSDMs were generally shifted towards positive values, we found a higher proportion of negative associations at fine spatial resolutions. Strikingly, estimates were not consistent across spatial scales and frequently switched between positive and negative values. Moreover, estimated species associations tended to be more positive for functionally similar species. Main conclusions: Our results show that species associations are more differentiated, that is, cover a broader range of values, at finer spatial resolutions. Yet, their positive correlation with functional similarity and the general over‐representation of positive associations suggest that shared responses to unobserved environmental predictors rather than biotic interactions underlie these scaling effects, cautioning against a naive interpretation of species associations estimated by JSDMs at any spatial scale. [ABSTRACT FROM AUTHOR]

Species distribution patterns are widely studied through species distribution models (SDMs), focusing mostly on climatic variables. Joint species distribution models (JSDMs) allow inferring if other factors (biotic interactions, shared phylogenetic history or other unmeasured variables) can also have an influence on species distribution. We identified current distributional areas and optimal suitability areas of three species of the solitary snail-shell bee Rhodanthidium (Hymenoptera: Megachilidae), and their host gastropod species in the Iberian Peninsula. We undertook SDMs using Maxent software, based on presence points and climatic variables. We also undertook JSDMs for the bees and the snails to infer if co-occurrence could be a result of biotic interactions. We found that the three bee species: (1) use at least five different species of Mediterranean snails; (2) use empty shells not only for nesting but also for sheltering when there is adverse weather and during the night; (3) have their most suitable areas in the eastern and southern Iberian Peninsula, mostly on limestone areas; and (4) have their optimal range under Mediterranean climatic values for the studied variables. There is positive co-occurrence of Rhodanthidium with the gastropod species, especially with the snail Sphincterochila candidissima. The contribution of the environmental component to the co-occurrence is less than that of the residual component in those cases, suggesting that: (i) the use of biotic resources (between Rhodanthidium and the gastropod species); (ii) shared phylogenetic history (between R. septemdentatum and R. sticticum); or (iii) unmeasured variables are largely responsible for cooccurrence. [ABSTRACT FROM AUTHOR]

Massive multiple-input and multiple-output is widely considered as a key enabler of the next generation 5G networks. With a large number of antennas at the base station, both spectral and energy efficiencies can be enhanced. Unfortunately, the downlink channel estimation overhead scales linearly with the number of antennas. This burden is easily mitigated in time division duplex systems by the use of the channel reciprocity property. However, this is unfeasible for frequency division duplex systems, and the method of two-stage beamforming was therefore developed to reduce the amount of channel state information feedback. The performance of this scheme being highly dependent on the users grouping and scheduling mechanisms, we introduce in this paper a new similarity measure coupled with a novel clustering procedure to achieve the appropriate users grouping. We also proceed to formulate the optimal users scheduling policy in joint spatial division and multiplexing (JSDM) and prove that it is NP-hard. This result is of paramount importance since it suggests that, unless P = NP, there are no polynomial time algorithms that solve the general scheduling problem to global optimality and the use of sub-optimal scheduling strategies is more realistic in practice. We, therefore, use graph theory to develop a sub-optimal users scheduling scheme that runs in polynomial time and outperforms the scheduling schemes previously introduced in the literature for JSDM in both sum-rate and throughput fairness. [ABSTRACT FROM AUTHOR]

Biotic interactions have been rarely included in traditional species distribution models, wherein joint species distribution models (JSDMs) emerge as a feasible approach to incorporate environmental factors and interspecific interactions simultaneously, making it a powerful tool for analyzing the structure and assembly processes of biotic communities. However, the predictability and statistical robustness of JSDMs are largely unknown because of the lack of research efforts for those newly developed models. This study systematically evaluated the performances of five JSDMs in predicting the occurrence and biomass of multiple species, with a particular focus on diverse characteristics of sampling data, including type of response variables, number of sampling sites, and the number of species included in models. In general, most models yielded satisfactory performances on fitting to observed data and on the estimation of environmental effects; however, they showed less well performances in evaluating species associations, and their predictability had large variations. The JSDMs showed inconsistent performances between the goodness‐of‐fit and predictability in cross‐validation, and the Boral model was relatively robust than others. The predictability of JSDMs was less influenced by sample sizes and substantially improved by incorporating rare species. This study contributes to an appropriate model selection and application of JSDMs. [ABSTRACT FROM AUTHOR]

Nematodes are involved in many important ecosystem functions such as nutrient cycling and plant growth. Nematode communities are thought to be structured at regional scales mainly by abiotic soil characteristics and climatic drivers and at local scales by habitat heterogeneity and biotic interactions. Blond dunes are dominated by marram grass (Calamagrostis arenaria), the key dune-forming plant species in Western Europe. Consequently, nematode food webs are mainly associated with marram grass in these coastal areas. We investigated the relative importance of regional biogeographic factors and local biotic drivers, such as the vegetation's spatial structure and the occurrence of an invasive plant species, in determining the functional diversity of belowground nematode communities inhabiting the roots of marram grass and surrounding soil in coastal dune areas. We found that nematode functional group abundances mainly differed among biogeographic regions, but that abundances could not be linked to plant-associated parameters, such as plant vitality or abundance. Additionally, the abundances of different functional groups seemed to be positively associated within both rhizosphere and bulk soil, an effect that could be the result of ecological filtering or facilitative interactions. Nematode pressure has been assumed to be an important driver of marram grass degeneration under ceasing sand dynamics. We here show that variation in nematode functional group composition is only weakly related to these local changes in plant vigour, but that large-scale patterns in nematode communities may explain regional variation in marram dynamics in coastal dunes. • Nematode functional groups react differently to local biotic drivers. • Roots and soil of marram grass host different, yet associated, nematode communities. • Strong positive correlations were found among soil and root functional groups. • Nematode composition showed thus regional top-down and local bottom-up structuring. [ABSTRACT FROM AUTHOR]

Understanding the patterns and drivers of species assemblages is the central tenet of community ecology and this may inform effective conservation and management strategies. Such information is scarce in tropical regions, particularly the Palawan faunal region and island group in the western Philippines. Here we examined the patterns of anuran richness and identified correlations in species co-occurrences and their shared responses to habitat types, water availability, and elevation. We sampled anuran populations using standardized transects established across Palawan's major islands between 2013 and 2019. We generated interpolated and extrapolated richness using Hill numbers. To investigate species co-occurrences and the relative importance of environmental variables, we used Joint Species Distribution Model (JSDM). A total of 18 anuran species were recorded, including seven non-endemic and 11 species restricted to Palawan. Anuran richness was highest in forests habitats than in cultivated land areas. Sites with water sources had higher anuran richness than those without water. Species richness observed along elevational gradient exhibited a hump-shaped pattern. Significant positive correlations in species co-occurrences were found among aquatic and semi-aquatic species. Anuran species showed tight associations with elevation and water availability, indicating that these variables are strong predictors of anuran co-occurrences. Finally, this study broadens our understanding of the differences and similarities in habitat requirements among anuran species, highlighting the need to consider such information when developing conservation strategies other than the traditional vulnerability and irreplaceability measures. • Water and elevation were strong predictors of anuran species co-occurrences. • Anuran richness was higher in forest habitats than in cultivated land areas. • A hump-shaped pattern of anuran richness was exhibited along elevational gradient. [ABSTRACT FROM AUTHOR]

Joint Spatial Division and Multiplexing (JSDM) is a downlink multiuser MIMO scheme recently proposed by the authors in order to enable “massive MIMO” gains and simplified system operations for Frequency Division Duplexing (FDD) systems. The key idea lies in partitioning the users into groups with approximately similar channel covariance eigenvectors and serving these groups by using two-stage downlink precoding scheme obtained as the concatenation of a pre-beamforming matrix, that depends only on the channel second-order statistics, with a multiuser MIMO linear precoding matrix, which is a function of the effective channels including pre-beamforming. The role of pre-beamforming is to reduce the dimensionality of the effective channel by exploiting the near-orthogonality of the eigenspaces of the channel covariances of the different user groups. This paper is an extension of our initial work on JSDM, and addresses some important practical issues. First, we focus on the regime of finite number of antennas and large number of users and show that JSDM with simple opportunistic user selection is able to achieve the same scaling law of the system capacity with full channel state information. Next, we consider the large-system regime (both antennas and users growing large) and propose a simple scheme for user grouping in a realistic setting where users have different angles of arrival and angular spreads. Finally, we propose a low-overhead probabilistic scheduling algorithm that selects the users at random with probabilities derived from large-system random matrix analysis. Since only the pre-selected users are required to feedback their channel state information, the proposed scheme realizes important savings in the CSIT feedback. [ABSTRACT FROM PUBLISHER]

• First evaluation of temporal transferability for joint species distribution models. • Build 36 models with different structures and complexity and 50 scenarios of time spans. • No modelling algorithm or level of complexity is superior. • Model structure and features of target species influence transferability in a contingent way. • Prolonging surveys alone is inefficient to improve transferability at the community level. Transferability of species distribution models is crucial for supporting biological conservation and management planning in the face of climate changes; however, there is a lack of understanding in how to achieve transference spatially and temporally, especially in a multispecies circumstance. This study evaluated the roles of model complexity and time scope in temporal transferability for multispecies distribution modelling. We collected data of multispecies distribution from a seven-year marine survey in coastal Yellow Sea, China, and used the data to evaluate the predictive performances of an array of multi-species distribution models (constrained linear ordination, constrained additive ordination, hierarchical models of species communities, multivariate random forests, multivariate tree boosting model, and multivariate artificial neural network), characterized by different structures, levels of complexity and time spans with 36 models and 50 scenarios. Our study showed that model transference was proper for some species but limited at the community level in general, and no specific modelling algorithm (regression models/machine-learning) or level of model complexity was found to be superior. Instead, model structure, features of target species, and time scope contributed substantially and influenced transferability in a contingent way. Temporal transferability tended to increase with the length of training periods and decay with the time gaps of prediction, whereas the magnitude varied among modelling algorithms. In addition, prolonging the time series of survey programs alone may have limited effectiveness on community-level transferability. This study contributes to the understanding of temporal transferability of multi-species distribution models and inform their applications in biological conservation and management from a temporal perspective. [ABSTRACT FROM AUTHOR]